BDA 503 Fall 2022

Lecture 7 (Dec 28, 2022)

Presentations!..

Lecture 6 (Dec 14, 2022)

Guest Lecture: Onur Karadeli - Head of Advanced Analytics, RPA, Big Data at SOCAR Turkey

This week’s lecture is about introduction to Operations Research and, if time permits, introduction to machine learning. Operations Research is both an historical and an emerging field of AI.

OR Assignment - Examine a Case (Deadline: Dec 30, 23:59)

In this individual assignment you are asked to choose a real life case study solved with Operations Research and briefly describe it with your own words.

Lecture 5 (Nov 30, 2022)

Guest Lecture: İhsancan Özpoyraz - Expert Business Consultant at KoçDigital

This week’s lecture is more about some intermediate topics about data processing/manipulation. We will mainly learn about joins, long/wide tables. In addition, if time permits, some data parsing from web site sources.

Lecture 4 (Nov 16, 2022)

Guest Lecture: Burak Balta - Partner & Lead Software Engineer at Sufle

This week’s lecture is focused on Shiny, an R package to develop interactive dashboards and web pages. Good news! Shiny became recently available for Python (alpha version), so what you learn here is transferrable to Python.

Additional resources

Shiny Assignment - Foreign Students by Nationality (Deadline: Nov 30, 18:30 Dec 4, 23:59)

In this assignment you are asked to prepare a Shiny dashboard using foreign student nationality data of universities taken from Higher Education Council’s (YÖK) statistics portal.

  • Download raw data (link).
  • Preprocess data (converting it to RDS format is recommended) to a workable data frame or tibble. You may work together .
  • Prepare a Shiny app as a single app.R file using the data add it to your progress journals under a separate folder with .
  • Deploy your app to shinyapps.io (use free tier only). (see documentation link)
  • Add a page to your progress journals with a short introduction of your assignment, a link to shinyapps url, a command to run your app locally. Example code snippet shiny::runGitHub("BOUN-IE48A/boun-ie48a.github.io",subdir="files/shinyExample/")

Lecture 3 (Nov 2, 2022)

Guest Lecture: Onur Soydan - Demand Forecasting and Strategic Planning Manager at Uludağ Enerji.

Group Assignment: Startup Deals (Deadline: 2022-11-16 18:30)

Your data set is a list of startups getting investments from a variety of domestic and international investors. Data is gathered from KPMG and 212’s Turkish Startup Investments Review 2021 report.

Your assignment is to tell the story of Turkish startup investments in 2021 using dplyr, ggplot2 and Quarto/Rmarkdown. Here are the rules and guidelines.

  • Download Startup Deals 2021 Data
  • Get the data in using readxl::read_excel() function (see tutorial).
  • Prepare an Exploratory Data Analysis (EDA) and put that analysis in your “Group Progress Journals (GPJ)”
  • Your EDA is graded based on the quality of your findings and the way you present them.
  • Your report should start with “Key Takeaways” (you need to put the exact title) section and it should include 3 to 5 bullets of short sentences about your most striking findings.
  • You should include at least one plot using ggplot2.
  • Your code should be visible and add the link to the data set (reproducibility). You may make code sections expandable in order to improve readability.
  • Add it on your Group Progress Journal. Your report should be reachable from your GPJ.

You are welcome to organize the rest of your report. You are free to determine the theme. For instance, you may focus on e-commerce investments only. You do not need to be comprehensive.

BONUS: Prepare a blog post for Medium without code and explain your analysis in two to three paragraphs.

Lecture 2 (Oct 19, 2022)

Lecture 1 (Oct 5, 2022)

Assignments

  • RMarkdown/Quarto Assignment (Deadline Oct 19, 18:30): This is your first assignment.

    1. Prepare an RMarkdown (.Rmd) or Quarto (.qmd) document. Introduce yourself in one paragraph (Your name surname, your work, your data interests and how you (plan to) use data science skills in your current/future work). Plus, add your Linkedin account link.
    2. Watch some UseR-2022 videos (Main Link - Recordings Link) and write one of them down on your RMarkdown/Quarto document. Alternatively you can check RStudio Global 2022 conference talks.
    3. Find 3 R posts relevant to your interests and describe them. Get the html output and put it in your progress journal repository.
    4. Provide a link from your Progress Journal page.

    Check examples from class of 2021: Emirhan Şahin, Mine Kara and Murat Can Taşar.

  • Project Groups (Deadline Nov 1, 17:30):

    1. Form your project groups of either 4 or 5 people (not fewer, not more). You may write to your instructor via Slack or email to find you a group or find a student for your group.
    2. Pick one of the group names below and email the instructor with your group name and members (first come first served). Remember, once set, you cannot change your group name or members.
      1. Western Shore
      2. Peace and Trust
      3. Silver Linings
      4. Whole Lotta Love
      5. Time and Space
      6. Ramble On
      7. Summer Moon
      8. Yellow Desert
      9. Honey Drip
      10. Rain Song

    Unassigned students and names will be randomly assigned by the instructor after the deadline.

Week 0

This course benefits from DataCamp for the Classroom program. See details here.

Some light reading (blog posts)

This semester course webpage went under a significant refurbishment. Course archive is in another repository.